Many applications, including applications associated with billing and expenses, rely on user entry for detail. However, users are not always complete and accurate in the entries that they make. In an attempt to remedy this, pervasive computing applications abound that allow point-of-event entry for these applications so that required entries are fresh in the user's mind, and entered data is more accurate and complete. This does not prevent lost entries, such as charges which are lost as people forget to report on lab tests or encounters with medical staff.
Examples of such applications include personal digital assistant (PDA) based expense accounts and products such as “Patient Keeper Charge Capture” available from Patient Keeper, Inc. of Brighton, Mass.
In specific applications, the time of reporting a specific occurrence can impact the cost and payments exchange between businesses. There are two types of existing billing systems:
(1) Real-time billing systems—These are billing systems where the payment is performed immediately at the time when the service is performed or goods are being purchased. Examples of a few types of real-time payment systems include: pre-paid phone cards; cash payments (e.g., to supermarkets, to physicians, for work, etc.); electronic wallet (e.g., smart cards) where money transactions are being exchanged; and parking tickets where exit point payment is required.
(2) Periodic billing systems—These are billing systems where the payment is being processed periodically at a later point in time to the time the service or goods were provided. Most billing systems work in this mode. In those cases, the transaction is fed into the system either manually or semi-manually. Examples of a few types of such payment systems include: regular phone bills, utility bills, healthcare insurance bills, expense accounts, police tickets, and ordering goods via phone or facsimile.
In all the above cases, the quality of the data entered manually depends on human ability to listen and see accurate information, as well as to type accurately. It is clear that errors can always occur as a result of human mistakes. Moreover, even in cases where systems can perform data cleansing and overcome some mistakes, timing can have an additional impact. Another example where timing can have significant impact on billing is related to hospitalization. Insurance companies have special controllers in hospitals that validate the time and reasons for hospitalization. Often today, the controllers must go back to their offices to report on hospitalization of their insured customers, and thus information is usually delayed by 24 hours. The temporal characteristic of the reporting event is critical to the cost calculation.
Filling in forms on the World Wide Web (e.g., using a personal computer) can be advantageous since logic programs can verify and check whether the form is filled in a reasonable manner. However, Web access is not always available, nor is simple verification sufficient for identifying all errors (especially errors of omission). Techniques in filling out electronic forms are well known and disclosed, for example, in U.S. Pat. No. 5,704,029 issued Dec. 30, 1997 to G. V. Wright, Jr., and entitled “System and Method for Completing an Electronic Form.”
Techniques to enhance form completion are also known in the art. For example, “cookies” are used to allow forms to be filled in on the Web with minimal additional data entry. Use of such cookies allows various techniques, such as prefix matching and attribute value pairs, in order to determine what data goes into what field.
Form filling can also be enhanced with location-based knowledge. For example, the U.S. patent application identified by U.S. Ser. No. 09/583,318, filed on May 20, 2000, and entitled “Method and System for Increasing Ease-of-Use and Bandwidth Utilization in Wireless Devices,” discloses using location to help determine entries a user may be trying to make on a wireless device (e.g., filling in a uniform resource locator (URL) with car price research sites when the user is standing in a used car lot).
Thus, in summary, data entry is often erroneous and subject to human error (e.g., incorrect information entry, partially incorrect information entry, failure to make an information entry). Whether paper or electronic, user error is responsible for many incorrect data records. What is needed is a technique for supplementing user entry with a validation data stream.